After deregulation, many U.S. airlines created hubs with banked schedules. However, in the past decade, these same airlines began to experiment with depeaking their schedules to reduce costs and to improve operational performance. Little research has investigated revenue shifts associated with depeaked schedules, yet an understanding of the tradeoffs between revenue, costs, and operational performance at a network level is critical before airlines will consider further depeaking and related strategies for managing congestion. This paper develops data-cleaning and data analysis methodologies that are based on publicly available data used to quantify airport- and network-level revenue changes associated with schedule depeaking. These methodologies are applied to a case study of Delta's depeaking at the airport in Atlanta, Georgia. Results show that this depeaking was associated with Delta's revenue increasing slower than that for the rest of the network and the industry as a whole but that the depeaking could have been profitable if costs had been cut to a sufficient degree. The Atlanta airport likely benefits from the increase in connection time. The methodologies developed in this paper can be extended to other depeaking cases to provide a comprehensive assessment of revenue shifts and to understand airport and network characteristics that are most conducive to schedule depeaking.